1. Click to edit Master title style Fire_CCI from Phase 1 to Phase 2 Itziar Alonso-Canas Emilio Chuvieco University of Alcalá

2. Click to edit Master title style Outline Each ECV project to describe current and planned applications for their data, and allow for discussion 1. Description of available data including: specification, validation, uncertainty, improvement of current state of the art 2. Current and planned applications of this data, including: C3S (copernicus climate change services), H2020 research, international initiatives, national programmes 3. Plans for products, delivery and engaging with climate researchers 4. Common issues between ECVs

3. Click to edit Master title style 3 years of MERIS data processed 2006- 2008 Pixel product : – Monthly files with date of detection. – Include confidence level and %cloud-free observations. – GeoTiff format Grid product: – 15-day files at 0.5 x 0.5 degree (CGM). – Include standard error and burned land cover. – NetCDF format. 1. Description of available data: specification - products

4. Click to edit Master title style 1. Description of available data: specification - products https://geogra.uah.es/esa/

5. Click to edit Master title style Reference fire perimeters derived from 105 Landsat TM/ETM+ image pairs Global validation performed for 2008, using probability sampling design, 2005-2009 temporal validation Validation based on cross tabulated error matrices 1. Description of available data: Validation Padilla et al, 2015 RSE

6. Click to edit Master title style Derived from 23 pairs of Landsat TM/ETM+ images from 2006 to 2008 not used in the validation – Pixel product: estimated in probabilistic terms (% confidence) based on regression analysis using as inputs CL of the classification, number of neighbour burned pixels and LC. – Grid product: similar model, output expressed as a standard error of the total burned area for each grid cell. 1. Description of available data: Uncertainty Alonso-Canas et al, 2015 RSE

7. Click to edit Master title style Adapted to climate modellers needs Higher spatial resolution (300m vs 500m) than other global BA products Detection of smaller fires (Randerson et al, 2012) Accuracy assessment: better balanced than the MODIS BA products (higher commission), less underestimation (relB = -34%, MCD64= 44% and MCD45= 48%). Significantly better than other European BA products (Geoland, GLOBCARBON and L3JRC) Assessment of its potential at regional and global scale 1. Description of available data: Improvement of CS of the art

8. Click to edit Master title style Global scale Close agreement with GFED4 in terms of spatial and temporal distribution. Mean annual burned area in the Fire_cci product was 369 Mha yr -1, 6.6 % higher than the estimated 346 Mha yr -1 of GFED4. Simulations with the ORCHIDEE model forced with the Fire_cci data yield comparable emissions to those of the GFED3 estimation -> The Fire_cci product is well suited for modelling fire emissions and related downstream studies of climatic effects.

9. Click to edit Master title style Products have different commission and omission errors depending on the region. Test if global products could be used to characterise regional fire regimes and fire shape Promising development of fire patch indices: fire model testing in DGVM Very useful to describe and better understand fire size and fire shape distributions at regional and global scale -> fire regime characterization and improvement in DGVMs. Regional scale

10. Click to edit Master title style Improvements in Phase 2 Process MERIS full time series Based on this algorithm (VNIR), develop a BA product from MODIS 250 m VNIR channels (current MODIS BA products use 500 m bands) Generating a small fire database for the African continent (also for other regions depending on data availability). The principal data sources for this work will be Landsat-8/OLI, Sentinel-2/MSI and Sentinel-1 SAR for very cloudy regions Extending time series (2000 – 2017) Adapt to S3 OLCI -> better temporal coverage Uncertainty

11. Click to edit Master title style 2. Current and planned applications of this data: Download of data from the web-> Planned: + 300 registered users GFED (emissions, deforestation,REDD, Carbon Cycle, DGVM).

12. Click to edit Master title style C3S: fire disturbance is one of the ECV’s foreseen in the services H2020: 2 proposals submitted – MyQube – Multiply International initiatives: – GOFC-GOLD – USGS ECV: implementation, validation 2. Current and planned applications of this data:

13. Click to edit Master title style 3. Plans for products, delivery and engaging with climate researchers

14. Click to edit Master title style CRG, CMUG Phase 2: – MPIC: IBBI, GEIA, MACC/CAMS, Core-Climax, CMIP6 – IRD: GEIA, ACCENT, FireMIP, CMIP6 – LSCE: FireMIP, GCP and GCP-RECCAP – VUA: GOFC-GOLD, GFED, FireMIP, GCP and GCP-RECCAP, CMIP6 End users: partner institutions from these activities include ECMWF, UK Metoffice, Juelich, Meteo France, Max Planck Institute for Meteorology, Max Planck Institute for Biogeochemistry, King’s College. External user group: MODIS team, FAO, INTA, JRC, CSIRO, INPE, natural hazards prevention community -> fire risk assessment 3. Plans for products, delivery and engaging with climate researchers

15. Click to edit Master title style 4. Common issues between ECVs Fire risk assesment: – Soil moisture – LST Fire emissions: – GHG – Ozone – Aerosol Deforestation fires: Land cover CCI

16. Click to edit Master title style 4. Common issues between ECVs Common sensors: – MERIS: LC_cci, Aerosol_cci – S2 data: LC_cci Common distribution interfaces: LC Water mask Cross-ECV checks to identify errors in the products, inconsistencies.

17. Click to edit Master title style Fire_CCI from Phase 1 to Phase 2 Itziar Alonso-Canas Emilio Chuvieco University of Alcalá